Design Process

We began the project with in-depth user research, analyzing the Excel-based process and identifying key pain points. Additionally, we conducted a thorough review of the existing legacy data log system. Feedback revealed that users struggled with navigation and found the interface overwhelming, highlighting the need for a more intuitive and efficient solution.

Data, Data, and more Data

I worked closely with the data engineering team to redesign the system, streamlining workflows and enhancing usability. We restructured features into intuitive categories, introduced a sidebar for quick access to essential tools, and optimized the entire process within months.

  • Designed a data-driven dashboard to display key metrics upfront for better visibility.

  • Simplified the user flow, reducing the number of clicks needed to complete tasks.

  • Implemented an AI-powered forecasting system that enabled real-time calculations in seconds.

AI 🤝 Design

After analyzing the data, we focused on transforming forecasting insights into a clear, user-friendly experience. To enhance usability, I implemented a minimalist design with a well-defined hierarchy, using color coding and typography to distinguish primary and secondary actions.

  • Built a comprehensive UI library to effectively visualize forecasting data.

  • Applied a streamlined design approach to maximize user efficiency and speed.

  • Optimized the ordering process, reducing turnaround time from one month to just five days.

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Results and Impact

Our team successfully streamlined 75+ Excel sheets into just three efficient processes, cutting a three-week workflow down to five days while improving accuracy from 78% to 90%. This transformation was so impactful that Toyota is now integrating additional legacy systems into the GPS application, further enhancing its supply chain. With Supply and Demand now optimized, the next phase focuses on advancing ordering and vehicle data systems to drive even greater efficiency.